import tensorflow as tf
import data_set
import load_data
import config as cfg


if __name__ == '__main__':
    l_d = load_data.LoadedData()
    l_d.load()
    l_d.norm()
    d_set = data_set.DataSet(l_d, cfg.batch_size)
    train_iter = d_set.train_gen()
    sess = tf.Session()
    next_item = train_iter.get_next()
    sess.run(train_iter.initializer)
    for _ in range(3):
        items = sess.run(next_item)
        # print(items)
        print(items[0].shape)
        print(items[1].shape)
        print(items[2].shape)
        print(items[3].shape)
        print(items[4].shape)
        print(items[5].shape)
        print()
